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使用基于微流控的单细胞转录分析评估细胞培养对原代组织样本中基因表达的影响。

Evaluating the Effect of Cell Culture on Gene Expression in Primary Tissue Samples Using Microfluidic-Based Single Cell Transcriptional Analysis.

作者信息

Januszyk Michael, Rennert Robert C, Sorkin Michael, Maan Zeshaan N, Wong Lisa K, Whittam Alexander J, Whitmore Arnetha, Duscher Dominik, Gurtner Geoffrey C

机构信息

Department of Surgery, Division of Plastic and Reconstructive Surgery, 257 Campus Drive West, Hagey Building GK-201, Stanford, CA 94305-5148, USA.

出版信息

Microarrays (Basel). 2015 Nov 4;4(4):540-50. doi: 10.3390/microarrays4040540.

DOI:10.3390/microarrays4040540
PMID:27600239
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4996408/
Abstract

Significant transcriptional heterogeneity is an inherent property of complex tissues such as tumors and healing wounds. Traditional methods of high-throughput analysis rely on pooling gene expression data from hundreds of thousands of cells and reporting a population-wide average that is unable to capture differences within distinct cell subsets. Recent advances in microfluidic technology have permitted the development of large-scale single cell analytic methods that overcome this limitation. The increased granularity afforded by such approaches allows us to answer the critical question of whether expansion in cell culture significantly alters the transcriptional characteristics of cells isolated from primary tissue. Here we examine an established population of human adipose-derived stem cells (ASCs) using a novel, microfluidic-based method for high-throughput transcriptional interrogation, coupled with advanced bioinformatic analysis, to evaluate the dynamics of single cell gene expression among primary, passage 0, and passage 1 stem cells. We find significant differences in the transcriptional profiles of cells from each group, as well as a considerable shift in subpopulation dynamics as those subgroups better able to adhere and proliferate under these culture conditions gradually emerge as dominant. Taken together, these findings reinforce the importance of using primary or very early passage cells in future studies.

摘要

显著的转录异质性是肿瘤和愈合伤口等复杂组织的固有特性。传统的高通量分析方法依赖于汇总来自数十万细胞的基因表达数据,并报告一个群体范围内的平均值,该平均值无法捕捉不同细胞亚群之间的差异。微流控技术的最新进展使得大规模单细胞分析方法得以发展,克服了这一局限性。这些方法提供的更高分辨率使我们能够回答一个关键问题,即细胞培养中的扩增是否会显著改变从原代组织分离的细胞的转录特征。在这里,我们使用一种基于微流控的新型高通量转录检测方法,并结合先进的生物信息学分析,来研究已建立的人脂肪来源干细胞(ASC)群体,以评估原代、第0代和第1代干细胞中单细胞基因表达的动态变化。我们发现每组细胞的转录谱存在显著差异,并且随着那些在这些培养条件下更能黏附并增殖的亚群逐渐成为优势亚群,亚群动态也发生了相当大的变化。综上所述,这些发现强化了在未来研究中使用原代或极早期传代细胞的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/b86e8603cad2/microarrays-04-00540-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/b11f7a10f536/microarrays-04-00540-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/2bdda4c63ed3/microarrays-04-00540-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/f82d2c5ec333/microarrays-04-00540-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/1d0fa13add3f/microarrays-04-00540-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/b86e8603cad2/microarrays-04-00540-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/b11f7a10f536/microarrays-04-00540-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/2bdda4c63ed3/microarrays-04-00540-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/f82d2c5ec333/microarrays-04-00540-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/1d0fa13add3f/microarrays-04-00540-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe71/4996408/b86e8603cad2/microarrays-04-00540-g005.jpg

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